Sunday, July 22

J.P. Morgan-backed start-up “goes galactic” with AI for FICC

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Mosaic Smart Data and the European Space Agency’s commercial arm have announced an alliance to advance the data analytics tools available to banks in the fixed income, currencies and commodities markets.

Last month, J.P. Morgan took a minority stake in Mosaic for an undisclosed sum.  The bank is also a client of data analytics firm, having put its platform into production within its rates business.

In this upcoming project, Mosaic will explore the potential for applying machine learning models developed and used by ESA in space systems to financial markets as well as further develop and share the algorithms with ESA for its own use.

The project will focus on data models used to identify patterns and correlations that are used by ESA for investigating anomalies of deep space satellite missions.

In financial markets, this technology may be highly effective in automatically identifying and creating hedging strategy recommendations, as well as giving sales and trading teams a much better indication of the market factors impacting their performance.

These models may also have applications in market surveillance by quickly identifying and flagging suspect trades and behaviour which may subtly fall outside a trader’s typical behaviour patterns.

“From fighting climate change to improving financial market surveillance, data analytics technology has the potential to radically reshape the way we approach challenges in many different industries,” said Matthew Hodgson, CEO of Mosaic Smart Data in a statement.

The first step will be a joint-funded feasibility study to see if ESA’s machine learning technology can benefit financial market participants. If successful, the technology will be built into Mosaic’s suite of analytics models.

Elia Montanari from the European Space Agency, added: “At the heart of ESA Business Applications is the aim of nurturing Europe’s most vibrant ventures that leverage space expertise and technology. This is a fascinating opportunity to look at how approaching data science problems in very different arenas – financial markets and space exploration – can lead to new, shared developments.”


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